Abstract

Default mode network (DMN) shows intrinsic, high-level activity at rest. We tested a hypothesis proposed for its role in sensory information processing: Intrinsic DMN activity facilitates neural responses to sensory input. A neural network model, consisting of a sensory network (Nsen) and a DMN, was simulated. The Nsen contained cell assemblies. Each cell assembly comprised principal cells, GABAergic interneurons (Ia, Ib), and glial cells. We let the Nsen carry out a perceptual task: detection of sensory stimuli. During DMN activation, glial cells were hyperpolarized by Ia-to-glia circuitry, by which glial membrane transporters imported GABA molecules from the extracellular space and decreased ambient GABA concentration. Acting on extrasynaptic GABA receptors, the decrease in ambient GABA concentration reduced inhibitory current in a tonic manner. This depolarized principal cells below their firing threshold during the ongoing spontaneous time period and accelerated their reaction speed to a sensory stimulus. During the stimulus presentation period, the Nsen inhibited the DMN and caused DMN deactivation. The DMN deactivation made Nsen Ia cells cease firing, thereby stopping the glial membrane hyperpolarization, quitting the GABA import, returning to the basal ambient GABA level, and thus enhancing global inhibition. Notably, the stimulus-relevant P cell firing could be maintained when GABAergic gliotransmission via Ia-glia signaling worked, decreasing ambient GABA concentration around the stimulus-relevant P cells. This enabled the Nsen to reliably detect the stimulus. We suggest that intrinsic default model network activity may accelerate the reaction speed of the sensory network by modulating its ongoing-spontaneous activity in a subthreshold manner. Ambient GABA contributes to achieve an optimal ongoing spontaneous subthreshold neuronal state, in which GABAergic gliotransmission triggered by the intrinsic default model network activity may play an important role.

1  Introduction

Noninvasive neuroimaging (e.g., functional magnetic resonance imaging, fMRI) studies identified a set of midline and lateral cortical brain regions known as default mode network (DMN) (Raichle et al., 2001). These regions show intrinsic, high-level activity at rest. Although the role of such intrinsic DMN activity in perceptual information processing is largely unknown, an interesting hypothesis has been proposed: intrinsic DMN activity may facilitate neuronal responses to sensory input (Raichle & Snyder, 2007). The purpose of this study is to test the hypothesis and elucidate its essential neuronal mechanisms. We simulate a neural network model that consists of a sensory network (Nsen) and a default mode network (DMN). The Nsen contains cell assemblies. Each cell assembly, comprising principal cells (P), GABAergic interneurons (Ia, Ib), and glial cells (glia), responds to one particular feature stimulus. The Nsen carries out a simple perceptual task: detection of sensory feature stimuli. P cells of the DMN send their axons to Ia cells of the Nsen, and P cells of the Nsen send their axons to Ib cells of the DMN.

The DMN shows a high level of firing activity in its P cells at rest (without sensory input). These P cells transmit action potentials to Ia cells of the Nsen, thereby inhibiting glial cells via Ia-to-glia circuitry. This lets glial membrane transporters import GABA molecules from the extracellular space and decreases ambient GABA concentration. Acting on extrasynaptic GABA receptors, the decrease of ambient GABA concentration reduces inhibitory current in a tonic manner. This depolarizes P cells below firing threshold: the DMN activates the Nsen in a subthreshold manner during the ongoing spontaneous time period prior to sensory stimulation.

Gamma-aminobutyric acid (GABA) is the major inhibitory neurotransmitter and mediates synaptic inhibition in a phasic manner, acting on intrasynaptic GABA receptors (i.e., GABA receptors in the synaptic cleft). So-called tonic inhibition occurs when extrasynaptic GABA activates receptors on membranes outside synapses (Semyanov, Walker, Kullmann, & Silver, 2004; Farrant & Nusser, 2005; Ortinski et al., 2006). GABA molecules in extracellular space and GABA receptors on extrasynaptic membrane regions are referred to as ambient GABA and extrasynaptic GABA receptor, respectively. Extrasynaptic GABA receptors have been found in the cerebellum (Somogyi, Takagi, Richards, & Mohler, 1989; Nusser, Roberts, Baude, Richards, & Somogyi, 1995; Brickley, Cull-Candy, & Farrant, 1996; Soltesz and Nusser, 2001) and the cortex (Drasbek & Jensen 2006; Scimemi et al. 2006).

In the brain, intrasynaptic GABA rises to a millimolar level triggered by a presynaptic action potential (Maconochie, Zempel, & Steinbach, 1994; Jones & Westbrook, 1995). In contrast, ambient GABA is maintained within a range of submicromolar to several micromolar levels (Lerma, Herranz, Herreras, Abraira, & Martin, 1986; Tossman, Jonsson, & Ungerstedt, 1986; Scimemi, Semyanov, Sperk, Kullmann, & Walker, 2005). The lower GABA level is sufficient to activate extrasynaptic but not intrasynaptic GABA receptors. GABA receptors containing the subunit, found in extrasynaptic membrane regions (Somogyi et al., 1989; Nusser et al., 1995; Brickley et al., 1996; Soltesz & Nusser, 2001), are known to have high affinity for GABA (Saxena & Macdonald, 1996; Brown, Kerby, Bonnert, Whiting, & Wafford, 2002) and little desensitization to continuous activation by GABA (Bianchim, Haas, & Macdonald, 2001, 2002). This leads to tonic inhibition of neurons even at lower ambient GABA levels.

We proposed a glial membrane transporter model in previous studies (Hoshino, 2012, 2013b; Zheng, Matsuo, Miyamoto, & Hoshino, 2014). We briefly explain it. Glial plasma membrane transporters such as GAT-1, GAT-2, and GAT-3 are known to regulate neuronal activity by modulating ambient GABA levels (Barakat & Bordey, 2002; Koch & Magnusson, 2009; Eulenburg & Gomeza, 2010). Experimental and theoretical studies by Richerson and colleagues (Richerson & Wu, 2003; Wu, Wang, & Richerson, 2003; Richerson, 2004; Wu, Wang, Diez-Sampedro, & Richerson, 2007) suggested that the GABA transporter could operate in an ion-coupled manner, pursuing an equilibrium point that is determined by the stoichiometry of transporter, the concentration gradients of substrates, and the plasma membrane potential. Under normal physiological conditions, a thermodynamic reaction cycle involves coupled translocation of two ions, one ion, and one uncharged GABA molecule. The cotransported molecules (2, , GABA) cross the membrane together. The driving force for the coupled transport is the electrochemical potential, which is the sum of the electropotential and the chemical potential.

The reversal potential of transporter is the equilibrium membrane voltage of glial cells at which the value of electrochemical potential is equal to 0. Under the normal physiological condition, the reversal potential was estimated to be 67.16.47 mV for cultured neurons (Wu et al., 2007), which we assume for glial cells. At glial membrane potentials below the reversal potential, net influx of GABA, called forward transport (i.e., GABA import), takes place. If membrane potential is above the reversal potential, net efflux of GABA, called reverse transport (i.e., GABA export), takes place.

A variety of neuron-glia circuits have been evidenced, including chemical (glutamate, GABA) synapses between presynaptic neurons and postsynaptic glial cells (for review, see Bezzi & Volterra, 2001; Fields & Stevens-Graham, 2002; Lin & Bergles, 2004; Overstreet, 2005). Based on these studies, we assume the Ia-to-glia (inhibitory) synaptic contact in the neural network model. Neuron-glia signaling that we neglect for simplicity includes GABA and glutamate signaling to glia through activation of metabotropic receptors (Verkhratsky, 2010; Velez-Fort, Audinat, & Angulo, 2012).

In the neural network model, when P cells of the Nsen are activated by sensory stimulation, they transmit action potentials to Ib cells of the DMN and inhibit its P cells via Ib-to-P circuitry, leading to DMN deactivation. This corresponds to a notion that the DMN is deactivated during perceptual tasks (Raichle et al., 2001). The DMN deactivation switches off the top-down DMN(P)-to-Nsen(Ia) excitation, depresses Ia-to-glia inhibition, and allows glial cells to be depolarized. The glial membrane depolarization makes their transporters quit importing GABA from the extracellular space, and thus ambient GABA concentration returns to the basal level. This increases extrasynaptic GABA receptor-mediated inhibitory current in P cells and suppresses the overall activity of the Nsen during the sensory stimulation period. Notably, the stimulus-relevant P cell firing can be maintained when GABAergic gliotransmission via Ia-glia signaling works, decreasing ambient GABA concentration around the stimulus-relevant P cells.

Concerning the top-down signaling from the default model network (DMN) to the sensory network (Nsen), primary sensory cortical areas are known to receive projections not only from primary thalamus but also from higher-order cortical areas (for review, see Harris & Mrsic-Flogel, 2013). These top-down projections arrive mostly in layer 1 (L1) of primary sensory cortical areas, where they synapse on interneurons and the apical dendrites of principal cells. Based on these observations, we assume the top-down projection from principal cells (P) of the DMN to interneurons (Ia) of the Nsen.

In this study, we record neuronal activities (membrane potentials and spikes) before and during exposure to sensory feature stimuli. We see how the Nsen responds to the stimuli and investigate how the intrinsic, high-level DMN activity affects the perceptual performance of the Nsen: detection of the stimuli. We make an additional simulation in which the intrinsic DMN activity depolarizes Nsen P cells below firing threshold in a phasic manner via P(DMN)-to-P(Nsen) circuitry. This alternative circuit, assumed based on Harris and Mrsic-Flogel (2013), excites P cells through glutamatergic neurotransmission and presumably gives a different effect. Comparing these two types of (i.e., tonic and phasic) top-down (DMN-to-Nsen) subthreshold excitatory effects, we try to elucidate how the intrinsic default model network activity facilitates responses of the sensory network to external input.

2  Neural Network Model

As shown in Figure 1A, the model consists of a sensory network (Nsen) and a default mode network (DMN). Cell assemblies of the Nsen () comprise principal cells (P), GABAergic interneurons (Ia, Ib), and glial cells (glia). Each cell assembly contains 20 cell units, with each cell unit comprising 1 P cell, 1 Ia cell, 1 Ib cell, and 1 glial cell. Each P cell receives excitatory inputs from other P cells and inhibitory inputs from Ib cells that receive excitatory inputs from P cells belonging to other cell assemblies. Each Ia cell receives an excitatory input from its accompanying P cell and synaptically connects to a glial cell. P cells receive an excitatory current as a sensory input when stimulated. For simplicity, the DMN has a single cell assembly, comprising P and Ib cells. P cells of the Nsen send axons to Ib cells of the DMN, and P cells of the DMN send axons to Ia cells of the Nsen.

Figure 1:

The neural network model. (A) Neuronal architecture. The model consists of a sensory network (Nsen) and a default mode network (DMN). Cell assemblies of the Nsen () comprise principal cells (P), GABAergic interneurons (Ia, Ib), and glial cells (glia). A single cell assembly, comprising P and Ib cells, constitutes the DMN. The open and filled triangles denote excitatory and inhibitory synapses, respectively. When presented with a feature stimulus fn, a constant excitatory current is applied as a sensory input to P cells belonging to cell assembly n. (B) A schematic illustration of GABA transport (Hoshino, 2012). Glial plasma membrane transporters import (remove) GABA molecules from the extracellular space when an Ia cell hyperpolarizes a glial cell. The ambient GABA molecules are accepted by extrasynaptic GABA receptors and tonically inhibit a P cell.

Figure 1:

The neural network model. (A) Neuronal architecture. The model consists of a sensory network (Nsen) and a default mode network (DMN). Cell assemblies of the Nsen () comprise principal cells (P), GABAergic interneurons (Ia, Ib), and glial cells (glia). A single cell assembly, comprising P and Ib cells, constitutes the DMN. The open and filled triangles denote excitatory and inhibitory synapses, respectively. When presented with a feature stimulus fn, a constant excitatory current is applied as a sensory input to P cells belonging to cell assembly n. (B) A schematic illustration of GABA transport (Hoshino, 2012). Glial plasma membrane transporters import (remove) GABA molecules from the extracellular space when an Ia cell hyperpolarizes a glial cell. The ambient GABA molecules are accepted by extrasynaptic GABA receptors and tonically inhibit a P cell.

When the Nsen is presented with a feature stimulus fn, P cells receive a graded (broadly tuned) sensory input. Namely, P cells belonging to cell assembly n receive the most intense input current, its neighbors (, ) the second most, and so on. The broadness of sensory input is determined by (see equation A.5 in appendix A). A conductance-based, integrate-and-fire neuron model (Hoshino, 2007a, 2007b, 2008) is employed.

Figure 1B shows a gliotransmission-mediated ambient GABA regulatory system (Hoshino, 2012). An Ia cell synaptically inhibits a glial cell. Transporters, which are embedded in the glial cell membrane, import (remove) GABA from the extracellular space when the Ia cell hyperpolarizes the glial cell. Ambient GABA molecules are accepted by extrasynaptic GABA receptors and tonically inhibit a P cell. For simplicity, extrasynaptic GABA receptors are located on P cells but not on Ia and Ib cells. The neural network model is described in appendixes A to C, whose parameters, and their values are listed in Table 1.

Table 1:
List of Parameters and Their Values.
DescriptionParameterValue
Membrane capacitance of type K (K = P, Ia, Ib, glia) cell   pF, pF, pF, pF 
Membrane conductance   nS, nS, nS, nS 
Resting potential   mV, mV 
Maximal conductance for type Z (Z = AMPA, GABA) receptor   nS, nS 
Reversal potential   
Number of cell units within cell assemblies N  
Number of cell assemblies M 
Synaptic weight (strength) from jth to ith P cell   
Synaptic weight from jth Ib to ith P cell  
Synaptic weight from ith P to Ia cell   
Synaptic weight from jth P cell of DMN to ith Ia cell of N  
Synaptic weight from ith P to Ib cell between different cell assemblies   
Synaptic weight from ith Ia to glial cell   
Synaptic weight from jth to ith P cell of DMN  
Synaptic weight from jth Ib to ith P cell of DMN   
Synaptic weight from jth P cell of N to ith Ib cell of DMN   
Amount of extrasynaptic GABA receptors on P cell   
Sensory input current  290 pA 
Broadness of sensory input   
Channel opening rate for type Z (Z = AMPA, GABA) receptor   
Channel closing rate   
Steepness of sigmoid function for type Y (Y = P, Ia, Ib) cell   
Threshold of sigmoid function   mV, mV, mV 
Decay constant for ambient GABA concentration  2.5 
Basal ambient GABA concentration  1
Maximal ambient GABA concentration  1.5
Minimal ambient GABA concentration  0
GABA transfer coefficient TGl  
Reversal potential of GABA transporter  −70 mV 
DescriptionParameterValue
Membrane capacitance of type K (K = P, Ia, Ib, glia) cell   pF, pF, pF, pF 
Membrane conductance   nS, nS, nS, nS 
Resting potential   mV, mV 
Maximal conductance for type Z (Z = AMPA, GABA) receptor   nS, nS 
Reversal potential   
Number of cell units within cell assemblies N  
Number of cell assemblies M 
Synaptic weight (strength) from jth to ith P cell   
Synaptic weight from jth Ib to ith P cell  
Synaptic weight from ith P to Ia cell   
Synaptic weight from jth P cell of DMN to ith Ia cell of N  
Synaptic weight from ith P to Ib cell between different cell assemblies   
Synaptic weight from ith Ia to glial cell   
Synaptic weight from jth to ith P cell of DMN  
Synaptic weight from jth Ib to ith P cell of DMN   
Synaptic weight from jth P cell of N to ith Ib cell of DMN   
Amount of extrasynaptic GABA receptors on P cell   
Sensory input current  290 pA 
Broadness of sensory input   
Channel opening rate for type Z (Z = AMPA, GABA) receptor   
Channel closing rate   
Steepness of sigmoid function for type Y (Y = P, Ia, Ib) cell   
Threshold of sigmoid function   mV, mV, mV 
Decay constant for ambient GABA concentration  2.5 
Basal ambient GABA concentration  1
Maximal ambient GABA concentration  1.5
Minimal ambient GABA concentration  0
GABA transfer coefficient TGl  
Reversal potential of GABA transporter  −70 mV 

3  Results

3.1  Influence of Intrinsic DMN Activity on Sensory Information Processing

Figure 2 shows fundamental dynamic characteristics of principal (P) cells of the DMN and Nsen (see Figure 2A), glial cells (see Figure 2B), and ambient GABA concentrations around P cells (see Figure 2C) belonging to respective cell assemblies (). The DMN shows a high-level activity at rest (without sensory input; see the top raster plot in Figure 2A). This activates Ia cells, and glial cells are hyperpolarized (see Figure 2B). The glial membrane hyperpolarization makes their transporters import GABA molecules from the extracellular space and decrease ambient GABA concentration (see Figure 2C). The basal ambient GABA concentration was (see equation C.1 in appendix C and Table 1).

Figure 2:

Responses to a feature stimulus. (A) Membrane potentials recorded from P cells belonging to respective cell assemblies (). f means a sensory feature that stimulates P cells belonging to cell assembly 3 of the Nsen. RT indicates reaction time to the input: f. (B) Glial membrane potentials. (C) Ambient GABA concentrations around P cells. means cell assembly 3, and the other cell assemblies 0, 1, 2, 4, 5, 6, and 7.

Figure 2:

Responses to a feature stimulus. (A) Membrane potentials recorded from P cells belonging to respective cell assemblies (). f means a sensory feature that stimulates P cells belonging to cell assembly 3 of the Nsen. RT indicates reaction time to the input: f. (B) Glial membrane potentials. (C) Ambient GABA concentrations around P cells. means cell assembly 3, and the other cell assemblies 0, 1, 2, 4, 5, 6, and 7.

When the network is presented with a feature stimulus (f3), DMN deactivation takes place (see the top raster plot in Figure 2A: input). This leads to deactivating Ia cells and allows glial cells to be depolarized toward the resting potential (see the traces for in Figure 2B). As a consequence, ambient GABA concentration returns toward the basal level (; see the traces marked with in Figure 2C), extrasynaptic GABA receptor-mediated inhibitory current is increased, and thus the firing activities of stimulus-irrelevant P cells are suppressed (see in Figure 2A).

The level of ambient GABA around stimulus-relevant P cells is kept low (see the trace marked with n = 3 in Figure 2C). This arises from the prevention of glial membrane depolarization (see n = 3 in Figure 2B). The low level of ambient GABA allows the stimulus-relevant P cells to be activated by the stimulus (see n = 3 in Figure 2A). Note that the stimulus-relevant P cells activate their accompanying Ia cells and inhibit the glial cells. Namely, the stimulus-relevant (n = 3) glial cells are prevented from depolarizing even when DMN deactivation takes place.

To see how the intrinsic DMN activity affects the perceptual performance of the Nsen, we cut the P(DMN)-to-Ia(Nsen) projection (see Figure 1A). As shown in Figure 3A, the reaction speed of the Nsen is decelerated: compare it with Figure 2A. The lack of DMN influence on the Nsen during the ongoing-spontaneous time period (before the sensory stimulation) makes Nsen Ia cells cease firing, thereby maintaining glial cells at the resting potential (see Figure 3B). Hence, ambient GABA concentration tends to be kept at the basal level (; see Figure 3C). This results in tonically inhibiting P cells, leading to the delay in their response to the applied stimulus (see RT in Figure 3A).

Figure 3:

Responses to a feature stimulus without DMN influence. The P(DMN)-to-Ia(Nsen) projection was cut. Conventions are identical to those in Figure 2.

Figure 3:

Responses to a feature stimulus without DMN influence. The P(DMN)-to-Ia(Nsen) projection was cut. Conventions are identical to those in Figure 2.

Figure 4A shows how the intrinsic DMN activity depolarizes P cells below their firing threshold and how to shorten the reaction time to the stimulus. As shown in Figure 4A (top; see the solid trace), the intrinsic DMN activity leads to a slight depolarization in P cells during the ongoing-spontaneous time period (before the sensory stimulation). The dashed trace represents that without DMN influence: P(DMN)-to-Ia(Nsen) was cut. Figure 4A (middle) presents distributions of these membrane potentials. Figure 4A (bottom) presents relationships of reaction time (left ordinate; see the circles) and average ongoing-spontaneous membrane potential (right ordinate; see the triangles) to connection weight from P cells of the DMN to Ia cells of the Nsen (: see equation A.9 and Table 1), indicating that the intrinsic DMN activity can accelerate the reaction speed of P cells by depolarizing them in a subthreshold manner during the ongoing-spontaneous time period.

Figure 4:

Ongoing-spontaneous subthreshold depolarization triggered by intrinsic DMN activity. (A) GABAergic gliotransmission-mediated tonic subthreshold excitation scheme worked. Top: Membrane activity of a P cell. The solid and dashed traces denote membrane potentials recorded with () and without () DMN influence, respectively. Middle: Distributions of ongoing-spontaneous membrane potentials. Bin size was 100 V. Bottom: Dependence of reaction time (left ordinate; see the circles) or average ongoing-spontaneous membrane potential (right ordinate; see the triangles) on connection weight from P cells of the DMN to Ia cells of the Nsen (P(DMN)-to-Ia(Nsen)): (see equation A.9 and Table 1). (B) Those when the glutamatergic neurotransmission-mediated phasic subthreshold excitation scheme worked. The original P(DMN)-to-Ia(Nsen) circuit was cut, and the alternative P(DMN)-to-P(Nsen) circuit was created. Conventions are identical to those in panel A. The connection weight from P cells of the DMN to P cells of the Nsen (P(DMN)-to-P(Nsen)) was varied (bottom).

Figure 4:

Ongoing-spontaneous subthreshold depolarization triggered by intrinsic DMN activity. (A) GABAergic gliotransmission-mediated tonic subthreshold excitation scheme worked. Top: Membrane activity of a P cell. The solid and dashed traces denote membrane potentials recorded with () and without () DMN influence, respectively. Middle: Distributions of ongoing-spontaneous membrane potentials. Bin size was 100 V. Bottom: Dependence of reaction time (left ordinate; see the circles) or average ongoing-spontaneous membrane potential (right ordinate; see the triangles) on connection weight from P cells of the DMN to Ia cells of the Nsen (P(DMN)-to-Ia(Nsen)): (see equation A.9 and Table 1). (B) Those when the glutamatergic neurotransmission-mediated phasic subthreshold excitation scheme worked. The original P(DMN)-to-Ia(Nsen) circuit was cut, and the alternative P(DMN)-to-P(Nsen) circuit was created. Conventions are identical to those in panel A. The connection weight from P cells of the DMN to P cells of the Nsen (P(DMN)-to-P(Nsen)) was varied (bottom).

We have achieved the ongoing-spontaneous subthreshold depolarization in P cells through GABAergic gliotransmission-mediated tonic excitation via P(DNN)-to-Ia(Nsen) circuitry (see Figure 2A). However, such a subthreshold depolarization is possible in another way: through glutamatergic neurotransmission-mediated phasic excitation via alternative P(DMN)-to-P(Nsen) circuitry. Figure 4B indicates that P cells of the Nsen can be depolarized in a phasic manner below firing threshold by the intrinsic DMN activity through P(DMN)-to-P(Nsen) excitation (top; see the solid trace). The dashed trace represents that without DMN influence: P(DMN)-to-P(Nsen) was cut. Figure 4B (middle) presents distributions of these membrane potentials. Figure 4B (bottom) presents relationships of reaction time (left ordinate; see the circles) and average ongoing-spontaneous membrane potential (right ordinate; see the triangles) to connection weight from P cells of the DMN to P cells of the Nsen, indicating poor acceleration of reaction speed compared to the original circuitry condition (see the circles at the bottom of Figure 4A).

3.2  How to Facilitate Neuronal Responses

In this section, we compare the GABAergic gliotransmission-mediated tonic subthreshold excitation scheme and glutamatergic neurotransmission-mediated phasic subthreshold excitation scheme in order to understand why the former led to the better enhancement in the reaction speed (see the circles in Figure 4A, bottom) than the latter (see the circles in Figure 4B, bottom).

Figure 5A (top) presents the relationship between reaction time and average ongoing spontaneous membrane potential, indicating that the acceleration of reaction speed is greater under the original circuitry condition (see the filled circles) than under the alternative circuitry condition (see the open circles). Figure 5A (bottom) presents reaction time (mean SD) for the alternative (see the open circle) or original (see the filled circles) circuitry condition, measured for the identical average ongoing spontaneous membrane potentials (66 mV: see the asterisk and sharp in the top panel of Figure 5A). In these measurements, we applied the same stimulus repeatedly (300 times) at different onset times. This result indicates that the GABAergic gliotransmission-mediated tonic subthreshold excitation scheme allows the Nsen to respond rapidly and reliably (with less variability) compared to the glutamatergic neurotransmission-mediated phasic subthreshold excitation scheme. Figure 5B shows the dependence of reaction time on basal ambient GABA concentration (see in equation C.1 and Table 1).

Figure 5:

Enhancement of reaction speed by GABAergic gliotransmission. (A) Top: Relationship between reaction time and average ongoing spontaneous membrane potential derived from those in Figures 4A (bottom) and 4B (bottom). The open and filled circles denote the alternative (glutamatergic neurotransmission-mediated phasic excitatory) and original (GABAergic gliotransmission-mediated tonic excitatory) circuitry conditions, respectively. Bottom: Reaction time (mean SD) measured for the identical average ongoing-spontaneous membrane potentials (−66 mV: see the asterisk and sharp in the top panel). (B) Dependence of reaction time on basal ambient GABA concentration (see in equation C.1 and Table 1) under the original (see the filled circles) or alternative (see the open circles) circuitry condition. (C) Modulation of ongoing-spontaneous membrane potential oscillation by intrinsic DMN activity. Top: Ongoing-spontaneous membrane potential recorded from a P cell under the original (see the solid trace) or alternative (see the dashed trace) circuitry condition. Middle: Distributions of ongoing-spontaneous membrane potentials. Bin size was 100 V. Bottom: Ongoing-spontaneous membrane potentials (mean SD).

Figure 5:

Enhancement of reaction speed by GABAergic gliotransmission. (A) Top: Relationship between reaction time and average ongoing spontaneous membrane potential derived from those in Figures 4A (bottom) and 4B (bottom). The open and filled circles denote the alternative (glutamatergic neurotransmission-mediated phasic excitatory) and original (GABAergic gliotransmission-mediated tonic excitatory) circuitry conditions, respectively. Bottom: Reaction time (mean SD) measured for the identical average ongoing-spontaneous membrane potentials (−66 mV: see the asterisk and sharp in the top panel). (B) Dependence of reaction time on basal ambient GABA concentration (see in equation C.1 and Table 1) under the original (see the filled circles) or alternative (see the open circles) circuitry condition. (C) Modulation of ongoing-spontaneous membrane potential oscillation by intrinsic DMN activity. Top: Ongoing-spontaneous membrane potential recorded from a P cell under the original (see the solid trace) or alternative (see the dashed trace) circuitry condition. Middle: Distributions of ongoing-spontaneous membrane potentials. Bin size was 100 V. Bottom: Ongoing-spontaneous membrane potentials (mean SD).

The question is why the original circuitry condition can lead to the better enhancement in the reaction speed than the alternative circuitry condition. To answer it, we recorded membrane potentials from a P cell during the ongoing-spontaneous time period for the two circuitry conditions. Note that their average values were almost identical (−66 mV: see the sharp and asterisk in the top panel of Figure 5A). As shown in Figure 5C (top), we found that the P cell transiently and frequently hyperpolarizes under the alternative circuitry condition (see the dashed trace) compared to the original circuitry condition (see the solid trace). Their membrane potential distributions are shown in Figure 5C (middle), indicating that the glutamatergic neurotransmission-mediated phasic subthreshold excitation scheme gives rise to frequent membrane hyperpolarizations (see the dashed trace) compared to the GABAergic gliotransmission-mediated tonic subthreshold excitation scheme (see the solid trace). Figure 5C (bottom) presents membrane potential (mean SD) for the alternative (see the open circle) or original (see the filled circle) circuitry condition. The less membrane hyperpolarization (see the solid traces in Figure 5C (top, middle) is reflected in a smaller standard deviation (SD; see the filled circle). These results indicate that the GABAergic gliotransmission-mediated tonic subthreshold excitation scheme allows P cells to oscillate with less transient hyperpolarization, thereby being able to respond rapidly and reliably to the sensory input (see the filled circle in Figure 5A, bottom).

Figure 6A shows membrane potential distributions for the original (left) and alternative (right) circuitry conditions. Note that GABAergic gliotransmission-mediated tonic subthreshold neuronal excitation took place under the original circuitry condition, and glutamatergic neurotransmission-mediated phasic subthreshold neuronal excitation took place under the alternative circuitry condition. The connection weight from the DMN to Nsen was varied. Each arrow indicates a maximal hyperpolarization potential and defines a hyperpolarization index. Figure 6B shows the relationship between reaction time and membrane hyperpolarization. Interestingly, even their mean potentials are identical (−66 mV: see the sharp and asterisk in panel A or in the top panel of Figure 5A), reaction time is longer under the alternative circuitry (or phasic excitatory) condition (see the asterisk in panel B) than under the original circuitry (or tonic excitatory) condition (see the sharp in panel B).

Figure 6:

Relationship between reaction time and membrane hyperpolarization. (A) Dependence of membrane potential distribution on the connection weight from the DMN to Nsen under the original (left: , i.e. P(DMN)-to-Ia(Nsen)) or alternative (right: P(DMN)-to-P(Nsen)) circuitry condition. An arrow indicates a maximal hyperpolarization potential, which we employ as a hyperpolarization index. (B) Relationship between reaction time and hyperpolarization index for the original (see the filled circles) or alternative (see the open circles) circuitry condition. The sharp and asterisk denote the almost identical mean membrane potentials (−66 mV: see the sharp and asterisk in panel A or in the top panel of Figure 5A).

Figure 6:

Relationship between reaction time and membrane hyperpolarization. (A) Dependence of membrane potential distribution on the connection weight from the DMN to Nsen under the original (left: , i.e. P(DMN)-to-Ia(Nsen)) or alternative (right: P(DMN)-to-P(Nsen)) circuitry condition. An arrow indicates a maximal hyperpolarization potential, which we employ as a hyperpolarization index. (B) Relationship between reaction time and hyperpolarization index for the original (see the filled circles) or alternative (see the open circles) circuitry condition. The sharp and asterisk denote the almost identical mean membrane potentials (−66 mV: see the sharp and asterisk in panel A or in the top panel of Figure 5A).

3.3  Coordination in Perceptual Performance by Intrinsic DMN Activity

In this section, we show how the Nsen responds when a broadly tuned sensory input is applied. The value of was increased from 0.1 to 4 (see equation A.5 and Table 1). As shown in Figure 7 (top), the Nsen responds incorrectly. That is, the stimulus-irrelevant P cells (see n = 4) generate action potentials, while the stimulus-relevant P cells (see n = 3) are silent. As shown in Figure 7 (bottom), the Nsen responds correctly to the stimulus by adding the P(DMN)-to-P(Nsen) connection to the original network (see the top panel). This result indicates that the P(DMN)-to-P(Nsen) connection works to eliminate perceptual errors when unsalient sensory information is available for the Nsen.

Figure 7:

Elimination of perceptual errors by glutamatergic neurotransmission-mediated phasic subthreshold neuronal excitation. Top: An example of an erroneous response where was increased from 0.1 to 4 (see equation A.5 and Table 1). GABAergic gliotransmission-mediated tonic subthreshold neuronal excitation (via P(DMN)-to-Ia(Nsen) circuitry) took place. The stimulus-irrelevant () but not stimulus-relevant () P cells respond. Bottom: P(DMN)-to-P(Nsen) connection was added to the original network (see panel A), whose weight was 0.25. Both GABAergic gliotransmission-mediated tonic subthreshold neuronal excitation (via P(DMN)-to-Ia(Nsen) circuitry) and glutamatergic neurotransmission-mediated phasic subthreshold neuronal excitation (via P(DMN)-to-P(Nsen) circuitry) took place. The stimulus-relevant () P cells become to respond.

Figure 7:

Elimination of perceptual errors by glutamatergic neurotransmission-mediated phasic subthreshold neuronal excitation. Top: An example of an erroneous response where was increased from 0.1 to 4 (see equation A.5 and Table 1). GABAergic gliotransmission-mediated tonic subthreshold neuronal excitation (via P(DMN)-to-Ia(Nsen) circuitry) took place. The stimulus-irrelevant () but not stimulus-relevant () P cells respond. Bottom: P(DMN)-to-P(Nsen) connection was added to the original network (see panel A), whose weight was 0.25. Both GABAergic gliotransmission-mediated tonic subthreshold neuronal excitation (via P(DMN)-to-Ia(Nsen) circuitry) and glutamatergic neurotransmission-mediated phasic subthreshold neuronal excitation (via P(DMN)-to-P(Nsen) circuitry) took place. The stimulus-relevant () P cells become to respond.

To see in detail how the intrinsic DMN activity affects the detection performance, we applied the same stimulus (f3) repeatedly (300 times) at different onset times and measured the rate of detection errors. Figure 8A shows the dependence of perceptual error rate on the broadness of sensory input (). Interestingly, we found that the glutamatergic neurotransmission-mediated phasic subthreshold excitation scheme works well for eliminating perceptual errors when the sensory input broadens (i.e., as increases; see the open circles) compared to the GABAergic gliotransmission-mediated tonic subthreshold excitation scheme (see the filled circles). Figure 8B shows how the input broadness affects the relationship between the perceptual error rate and the connection weight from P cells of the DMN to Ia cells of the Nsen (original circuitry condition: left) or the connection weight from P cells of the DMN to P cells of the Nsen (alternative circuitry condition: right). Figure 8C shows how the input broadness affects the relationship between the perceptual error rate and the basal ambient GABA level under the original (left) or alternative (right) circuitry condition.

Figure 8:

Dependence of neuronal responses on the broadness of sensory input. (A) Perceptual error rate as a function of the broadness of sensory input (: see equation A.5 and Table 1). The filled and open circles denote the original and alternative circuitry conditions, respectively. Note that GABAergic gliotransmission-mediated tonic subthreshold neuronal excitation took place under the original circuitry condition, and glutamatergic neurotransmission-mediated phasic subthreshold neuronal excitation took place under the alternative circuitry condition. (B) Influence of the input broadness () on the relationship between the perceptual error rate and the connection weight from P cells of the DMN to Ia cells of the Nsen (original circuitry condition: left) or the connection weight from P cells of the DMN to P cells of the Nsen (alternative circuitry condition: right). (C) Influence of the input broadness () on the relationship between the perceptual error rate and the basal ambient GABA concentration under the original (left) or alternative (right) circuitry condition.

Figure 8:

Dependence of neuronal responses on the broadness of sensory input. (A) Perceptual error rate as a function of the broadness of sensory input (: see equation A.5 and Table 1). The filled and open circles denote the original and alternative circuitry conditions, respectively. Note that GABAergic gliotransmission-mediated tonic subthreshold neuronal excitation took place under the original circuitry condition, and glutamatergic neurotransmission-mediated phasic subthreshold neuronal excitation took place under the alternative circuitry condition. (B) Influence of the input broadness () on the relationship between the perceptual error rate and the connection weight from P cells of the DMN to Ia cells of the Nsen (original circuitry condition: left) or the connection weight from P cells of the DMN to P cells of the Nsen (alternative circuitry condition: right). (C) Influence of the input broadness () on the relationship between the perceptual error rate and the basal ambient GABA concentration under the original (left) or alternative (right) circuitry condition.

4  Discussion

We showed that subthreshold excitation of the sensory network by the default mode network could accelerate the reaction speed of the sensory network to external input. This supports the hypothesis proposed by Raichle and Snyder (2007): intrinsic DMN activity may facilitate neuronal responses to sensory input. We investigated its essential neuronal mechanisms. The conclusions are as follows:

  1. Intrinsic default mode network activity may accelerate the reaction speed of the sensory network by tonically exciting its ongoing spontaneous neuronal activity in a subthreshold manner.

  2. GABAergic gliotransmission, triggered by intrinsic default model network activity, may regulate ambient GABA concentration in order to achieve an optimal ongoing-spontaneous subthreshold neuronal state in the sensory network.

  3. Glutamatergic neurotransmission-mediated phasic subthreshold neuronal excitation may contribute to eliminating perceptual errors when unsalient sensory information is available for the sensory cortex.

We suggest that the brain may coordinate the GABAergic gliotrans-mission-mediated tonic subthreshold neuronal excitation and the glutamatergic neurotransmission-mediated phasic subthreshold neuronal excitation in order to cope with a variety of sensory information.

We showed that a reduction in ambient GABA concentration contributed to facilitating neuronal responses to sensory input. A recent study (Maya-Vetencourt et al., 2012) demonstrated that the visual cortex of rats treated by insulin-like growth factor (IGF-1) showed a reduction in ambient GABA concentration. Interestingly, this treatment enhanced synaptic plasticity in adult rats, which might be beneficial for improving their perceptual performance. We suggest an experiment demonstrating how the level of ambient GABA affects the responsiveness of visual cortical neurons to sensory (visual) stimuli.

In the model presented here, the sensory network and the default mode network were directly connected. Experimental studies indicated that sensory network activity was simultaneously coupled with default mode network activity (for a review, see Anticevic et al., 2012). Such coupling might be achieved directly or indirectly. Although, to the best of our knowledge, there is no clear anatomical evidence of direct coupling, we assumed a minimal-size model with a direct connection between the sensory network and the default mode network in order to achieve the functional connectivity between these two networks. It was enough to investigate how the intrinsic default mode network activity facilitates responses of the sensory network to external input.

In this study, we employed two biologically plausible schemes in order to test the hypothesis proposed by Raichle and Snyder (2007): intrinsic DMN activity may facilitate neuronal responses to sensory input. One was GABAergic gliotransmission-mediated tonic subthreshold neuronal excitation, and the other was glutamatergic neurotransmission-mediated phasic subthreshold neuronal excitation. The former worked under the original circuitry condition and the latter under the alternative circuitry condition. Compared to the glutamatergic neurotransmission mechanism, the GABAergic gliotransmission mechanism could excite principal cells in a subthreshold manner with less membrane fluctuation, that is, with less transient membrane hyperpolarization. This enabled the principal cells to generate persistent spikes responding to sensory input. Note that the membrane hyperpolarization resulted in breaking the persistent neuronal firing, leading to a delay in response.

Although we discussed in detail limitations of the sensory network (Nsen) model in our previous study (Hoshino, 2012), we briefly address them here. Glial cells might have a role in regulating extracellular concentrations of transmitters (GABA, glutamate), ions (potassium, hydrogen, calcium), and metabolites (ATP) (Fields & Stevens-Graham, 2002; Newman, 2003; Hansson & Rönnbäck, 2003; Verkhratsky, 2010). In this study, we focused on investigating how ambient GABA-mediated intracortical inhibition, coordinated by the DMN, affects sensory information processing. We could model a glial plasma membrane transporter that regulates an ambient GABA level because the mechanism of GABA transport had been theoretically explained (Richerson & Wu, 2003; Richerson, 2004; Wu et al., 2007).

We did not model those that regulate extracellular levels of glutamate and potassium, because their transport mechanisms are not yet fully understood. For instance, several lines of evidence indicate that a calcium-dependent exocytotic process can transport glutamate; however, its precise mechanism is unknown (for a review, see Newman, 2003). Glial cells are probably the source of GABA responsible for extrasynaptic GABA receptor-mediated inhibitory current and can transport different transmitters (Kozlov, Angulo, Audinat, & Charpak, 2006; Angulo, Le Meur, Kozlov, Charpak, & Audinat, 2008). The question remains: How could each of these different types of gliotransmission be controlled? We proposed in a previous study (Hoshino, 2013b) a working hypothesis: GABAergic gliotransmission prevails in information processing in primary sensory cortices, for which suitable spatial organization of glial cells is required.

Appendix A:  The Neural Network Model

For the sensory network (Nsen), dynamic evolution of membrane potential of the ith P cell that belongs to cell assembly n is defined by
formula
A.1
where is an excitatory synaptic current from other P cells, an inhibitory synaptic current from Ib cells, an inhibitory nonsynaptic current mediated by ambient GABA via extrasynaptic receptors, and an excitatory input current that is provided when presented with sensory feature finp: . These currents are defined by
formula
A.2
formula
A.3
formula
A.4
formula
A.5
Dynamic evolution of membrane potential of the ith Ia and Ib cells that belong to cell assembly n is defined by
formula
A.6
formula
A.7
where and are excitatory synaptic currents from P cells. is an excitatory synaptic current from P cells of the default mode network (DMN). These currents are defined by
formula
A.8
formula
A.9
formula
A.10
Dynamic evolution of the membrane potential of the ith glial cell that belongs to cell assembly n is defined by
formula
A.11
where is an inhibitory synaptic current from an Ia cell. This current is defined by
formula
A.12

In these equations, is the fraction of AMPA receptors in the open state triggered by presynaptic action potentials of the jth P cell, and is that by the jth P cell of the DMN. and are the fractions of intrasynaptic GABA receptors in the open state triggered by presynaptic action potentials of the jth Ib cell and Ia cell, respectively. is the fraction of extrasynaptic GABA receptors, located on the ith P cell, in the open state provoked by ambient GABA. The receptor dynamics and ambient GABA concentration dynamics are defined in appendixes B and C.

For simplicity, the DMN comprises P and Ib cells. For model parameters and their values, see Table 1.

Appendix B:  Receptor Dynamics and Action Potential Generation

Receptor dynamics is based on a study (Destexhe, Mainen, & Sejnowski, 1998) and described as
formula
B.1
formula
B.2
formula
B.3
where and are concentrations of glutamate and GABA in synaptic clefts, respectively. = 1 mM and = 1 mM for 1 msec when the presynaptic jth P cell and type X cell fire, respectively. Otherwise, = 0 and = 0. Concentration of ambient GABA, , is defined in appendix C.
The probability of neuronal firing is defined by
formula
B.4
When a cell fires, its membrane potential is depolarized to −10 mV, which is kept for 1 msec and then reset to the resting potential. For model parameters and their values, see Table 1.

Appendix C:  Dynamics of Ambient GABA Concentration

Concentration of ambient GABA around the ith P cell that belongs to cell assembly n is defined by
formula
C.1
For the details of model parameters and their values, see Table 1 and our previous studies (Hoshino, 2009, 2010, 2011a, 2011b, 2012, 2013a). The simulation was made by numerical calculation of these differential equations. C language and the Runge-Kutta algorithm was employed where the time step size was 100 microseconds.

Acknowledgments

We express our gratitude to Takeshi Kambara and Masayoshi Naito for their helpful discussions and to reviewers for giving us valuable comments and suggestions.

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